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[General] Salesforce-AI-Specialist Exam Simulator Fee | Exam Salesforce-AI-Specialist Trai

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【General】 Salesforce-AI-Specialist Exam Simulator Fee | Exam Salesforce-AI-Specialist Trai

Posted at 1/26/2026 08:44:27      View：59 | Replies：0        Print      Only Author   [Copy Link] 1#
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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:
TopicDetails
Topic 1
  • Agentforce Tools: In this topic, AI specialists get knowledge using agents when it is appropriate. Moreover, the topic explains the working of agents and reasoning engine powers Agentforce. Lastly, the topic focuses on managing and monitoring agent adoption.
Topic 2
  • Einstein Trust Layer: This section evaluates the skills of Salesforce AI specialists responsible for implementing security protocols and safeguarding data privacy. It emphasizes the security, privacy, and foundational features of the Einstein Trust Layer.
Topic 3
  • Prompt Builder: This section evaluates the expertise of AI specialists working with Salesforce's AI tools. It focuses on the Prompt Builder feature, requiring candidates to understand its usage based on business needs.
Topic 4
  • Model Builder: This portion of the exam focuses on Salesforce AI specialists' expertise in working with AI models within Salesforce environments. Candidates will need to demonstrate knowledge of when to use the Model Builder and how to configure standard, custom, or Bring Your Own Large Language Model (BYOLLM) generative models to meet business needs.
Topic 5
  • Generative AI in CRM Applications: This part of the exam assesses AI specialists’ knowledge of generative AI within CRM systems. It covers the use of generative AI features in Einstein for Sales and Einstein for Service.

Salesforce Certified AI Specialist Exam Sample Questions (Q81-Q86):NEW QUESTION # 81
When a customer chat is initiated, which functionality in Salesforce provides generative AI replies or draft emails based on recommended Knowledge articles?
  • A. Einstein Service Replies
  • B. Einstein Grounding
  • C. Einstein Reply Recommendations
Answer: A
Explanation:
When a customer chat is initiated, Einstein Service Replies provides generative AI replies or draft emails based on recommended Knowledge articles. This feature uses the information from the Salesforce Knowledge base to generate responses that are relevant to the customer's query, improving the efficiency and accuracy of customer support interactions.
Option B is correct because Einstein Service Replies is responsible for generating AI-driven responses based on knowledge articles.
Option A (Einstein Reply Recommendations) is focused on recommending replies but does not generate them.
Option C (Einstein Grounding) refers to grounding responses in data but is not directly related to drafting replies.
Reference:
Einstein Service Replies Overview: https://help.salesforce.com/s/ar ... service_replies.htm

NEW QUESTION # 82
What is an AI Specialist able to do when the "Enrich event logs with conversation data" setting in Einstein Copilot is enabled?
  • A. View session data including user Input and copilot responses for sessions over the past 7 days.
  • B. Generate details reports on all Copilot conversations over any time period.
  • C. View the user click path that led to each copilot action.
Answer: A
Explanation:
When the "Enrich event logs with conversation data" setting is enabled in Einstein Copilot, it allows an AI Specialist or admin to view session data, including both the user input and copilot responses from interactions over the past 7 days. This data is crucial for monitoring how the copilot is being used, analyzing its performance, and improving future interactions based on past inputs.
This setting enriches the event logs with detailed conversational data for better insights into the interaction history, helping AI specialists track AI behavior and user engagement.
Option A, viewing the user click path, focuses on navigation but is not part of the conversation data enrichment functionality.
Option C, generating detailed reports over any time period, is incorrect because this specific feature is limited to data for the past 7 days.
Salesforce AI Specialist Reference:
You can refer to this documentation for further insights: https://help.salesforce.com/s/ar ... t_event_logging.htm

NEW QUESTION # 83
Universal Containers' current AI data masking rules do not align with organizational privacy and security policies and requirements.
What should an AI Specialist recommend to resolve the issue?
  • A. Configure data masking in the Einstein Trust Layer setup.
  • B. Add new data masking rules in LLM setup.
  • C. Enable data masking for sandbox refreshes.
Answer: A
Explanation:
WhenUniversal Containers' AI data masking rulesdo not meet organizational privacy and security standards, the AI Specialist should configure thedata maskingrules within theEinstein Trust Layer. The Einstein Trust Layerprovides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
* Option A, enabling data masking for sandbox refreshes, is related to sandbox environments, which are separate from how AI interacts with production data.
* Option C, adding masking rules in the LLM setup, is not appropriate because data masking is managed through theEinstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the AI model and ensures compliance with privacy regulations.
Salesforce AI Specialist References:For more information, refer to:https://help.salesforce.com/s/articleView?
id=sf.einstein_trust_layer_data_masking.htm

NEW QUESTION # 84
An administrator is responsible for ensuring the security and reliability of Universal Containers' (UC) CRM dat a. UC needs enhanced data protection and up-to-date AI capabilities. UC also needs to include relevant information from a Salesforce record to be merged with the prompt.
Which feature in the Einstein Trust Layer best supports UC's need?
  • A. Zero-data retention policy
  • B. Data masking
  • C. Dynamic grounding with secure data retrieval
Answer: C
Explanation:
Dynamic grounding with secure data retrieval is a key feature in Salesforce's Einstein Trust Layer, which provides enhanced data protection and ensures that AI-generated outputs are both accurate and securely sourced. This feature allows relevant Salesforce data to be merged into the AI-generated responses, ensuring that the AI outputs are contextually aware and aligned with real-time CRM data.
Dynamic grounding means that AI models are dynamically retrieving relevant information from Salesforce records (such as customer records, case data, or custom object data) in a secure manner. This ensures that any sensitive data is protected during AI processing and that the AI model's outputs are trustworthy and reliable for business use.
The other options are less aligned with the requirement:
Data masking refers to obscuring sensitive data for privacy purposes and is not related to merging Salesforce records into prompts.
Zero-data retention policy ensures that AI processes do not store any user data after processing, but this does not address the need to merge Salesforce record information into a prompt.
Reference:
Salesforce Developer Documentation on Einstein Trust Layer
Salesforce Security Documentation for AI and Data Privacy

NEW QUESTION # 85
A Salesforce Administrator is exploring the capabilities of Einstein Copilot to enhance user interaction within their organization. They are particularly interested in how Einstein Copilot processes user requests and the mechanism it employs to deliver responses. The administrator is evaluating whether Einstein Copilot directly interfaces with a large language model (LLM) to fetch and display responses to user inquiries, facilitating a broad range of requests from users.
How does Einstein Copilot handle user requests In Salesforce?
  • A. Einstein Copilot will perform an HTTP callout to an LLM provider.
  • B. Einstein Copilot analyzes the user's request and LLM technology is used to generate and display the appropriate response.
  • C. Einstein Copilot will trigger a flow that utilizes a prompt template to generate the message.
Answer: B
Explanation:
Einstein Copilot is designed to enhance user interaction within Salesforce by leveraging Large Language Models (LLMs) to process and respond to user inquiries. When a user submits a request, Einstein Copilot analyzes the input using natural language processing techniques. It then utilizes LLM technology to generate an appropriate and contextually relevant response, which is displayed directly to the user within the Salesforce interface.
Option C accurately describes this process. Einstein Copilot does not necessarily trigger a flow (Option A) or perform an HTTP callout to an LLM provider (Option B) for each user request. Instead, it integrates LLM capabilities to provide immediate and intelligent responses, facilitating a broad range of user requests.
Reference:
Salesforce AI Specialist Documentation - Einstein Copilot Overview: Details how Einstein Copilot employs LLMs to interpret user inputs and generate responses within the Salesforce ecosystem.
Salesforce Help - How Einstein Copilot Works: Explains the underlying mechanisms of how Einstein Copilot processes user requests using AI technologies.

NEW QUESTION # 86
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